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Abstract

Background

The PRKAG3 gene encodes the γ3 subunit of adenosine monophosphate activated protein kinase (AMPK), a protein that plays a key role in energy metabolism in skeletal muscle. Non-synonymous
single nucleotide polymorphisms (SNPs) in this gene such as I199V are associated with important pork quality traits. The objective of this study was
to investigate the relationship between gene expression of the PRKAG3 gene, SNP variation in the PRKAG3 promoter and meat quality phenotypes in pork.

Results

PRKAG3 gene expression was found to correlate with a number of traits relating to glycolytic
potential (GP) and intramuscular fat (IMF) in three phenotypically diverse F1 crosses
comprising of 31 Large White, 23 Duroc and 32 Pietrain sire breeds. The majority of
associations were observed in the Large White cross. There was a significant association
between genotype at the g.-311A>G locus and PRKAG3 gene expression in the Large White cross. In the same population, ten novel SNPs
were identified within a 1.3 kb region spanning the promoter and from this three major
haplotypes were inferred. Two tagging SNPs (g.-995A>G and g.-311A>G) characterised
the haplotypes within the promoter region being studied. These two SNPs were subsequently
genotyped in larger populations consisting of Large White (n = 98), Duroc (n = 99)
and Pietrain (n = 98) purebreds. Four major haplotypes including promoter SNP’s g.-995A>G
and g.-311A>G and I199V were inferred. In the Large White breed, HAP1 was associated with IMF% in the M. longissmus thoracis et lumborum (LTL) and driploss%. HAP2 was associated with IMFL% GP-influenced traits pH at 24
hr in LTL (pHULT), pH at 45 min in LTL (pH45LT) and pH at 45 min in the M. semimembranosus muscle (pH45SM). HAP3 was associated with driploss%, pHULT pH45LT and b* Minolta. In the Duroc breed, associations were observed between HAP1 and
driploss% and pHUSM. No associations were observed with the remaining haplotypes (HAP2,
HAP3 and HAP4) in the Duroc breed. The Pietrain breed was monomorphic in the promoter
region. The I199V locus was associated with several GP-influenced traits across all three breeds and
IMF% in the Large White and Pietrain breed. No significant difference in promoter
function was observed for the three main promoter haplotypes when tested in vitro.

Conclusion

Gene expression levels of the porcine PRKAG3 are associated with meat quality phenotypes relating to glycolytic potential and
IMF% in the Large White breed, while SNP variation in the promoter region of the gene
is associated with PRKAG3 gene expression and meat quality phenotypes.

Keywords:

Background

Adenosine monophosphate activated protein kinase (AMPK) is a heterodimeric serine/threonine protein kinase. This enzyme is a metabolic master
regulator of several intracellular pathways, including cellular uptake of glucose,
glycogen synthesis and β-oxidation of fatty acids, controlling metabolism through
transcription and direct effects on metabolic enzymes [1-3]. AMPK is composed of a catalytic α-subunit and two regulatory non-catalytic β- and γ- subunits.
A specific isoform of the regulatory γ subunit of AMPK (AMPK γ3) has a role in the metabolic plasticity of fast-glycolytic muscle [4]. The AMPK γ3 isoform is encoded by the highly conserved PRKAG3 gene and is primarily expressed in white (fast-twitch, type IIb) skeletal muscle
fibers [5,6]. Gain of function mutations in the PRKAG3 gene have been correlated with increased glycogen content in skeletal muscle in pig
[7,8], mice [9] and humans [10]. The metabolic consequences of these mutations extend beyond glycogen metabolism
however, and can also influence other characteristics of the muscle, including mitochondrial
biogenesis [11], fatty acid uptake [10,12] oxidative capacity [12] and differential responses to exercise [8].

Five non-synonymous substitutions (T30N, G52S, L53P, I199V and R200Q) have been reported in the porcine PRKAG3 gene [7,13,14]. The effects of I199V and R200Q are the most widely studied. Both mutations are located in a highly conserved region
of the cystathionine β- synthase domain [13] which is believed to act as a sensor of cellular energy status [15]. The R200Q polymorphism has been linked to a 70% increase in glycogen content in the skeletal
muscle of Hampshire pigs. The resultant alteration in GP affects meat quality traits
including water holding capacity (drip loss%) and pH, as well as processing yields
[13], but the SNP has largely been eliminated from breeding populations [16]. The adjacent polymorphism I199V[7] has also been associated with glycolytic traits including water holding capacity
[17] and pH [18]. The minor I allele is widely reported to have positive effect on pH and water holding
capacity in diverse pig breed populations [7,17-19]. The physiological functions of PRKAG3 contribute to a wider range of pork quality characteristics including colour [18,20,21], carcass composition [22,23], seasoning losses [24] and IMF% [25,26].

Preliminary data from our group has suggested that the PRKAG3 gene is differentially expressed in LTL muscle of pigs displaying extremes in the
distribution of drip loss% values in a Large White population [27]. Hence, our first objective was to test for an association between PRKAG3 gene expression and pigmeat quality phenotypes, with a focus on GP-influenced traits
and IMF%. This was performed in 3 sire breeds (Large White, Duroc and Pietrain) that
are divergent in their muscle and meat quality characteristics [28]. Alterations in gene expression can be caused by genetic variation in the regulatory
regions of the gene [29-31]. Hence, the second objective was to identify novel genetic variation in the PRKAG3 gene promoter region. The final objective was to examine if the identified allelic
variants differed in promoter function by: a) testing for association between novel
SNPs/haplotypes and gene expression and pork quality traits, and b) investigating
how haplotype variation affects putative transcription factor binding sites in silico and promoter function in vitro.

Results

Relationship between PRKAG3 expression and pork quality phenotypes

A number of correlations were identified between PRKAG3 [GenBank; NM_214077.1] expression levels in the LTL muscle and meat quality phenotypes
which are known to be influenced by glycolytic potential in the muscle (termed GP-influenced
traits) in the F1 crossbred pig populations (Table 1). The Large White population displayed the greatest number of significant correlations,
with a smaller number of correlations observed in the Duroc cross breed, while none
were observed in the Pietrain cross breed. In the Large White cross breed a number
of traits were positively correlated with PRKAG3 gene expression including water holding capacity measures driploss% and cookloss%.
ECULT and colour Minolta L* were also positively correlated with PRKAG3 gene expression while pHULT was negatively correlated. A smaller number of correlations
with GP- influenced traits were evident in the Duroc cross breed including pHULT (negative)
and Minolta L* on Day 7 (positive). IMF % was also positively correlated with PRKAG3 gene expression in the Large White cross breed.

SNP Discovery and identification of tagging SNPs

Sequencing of the 1322 bp upstream region revealed 10 novel SNPs (Figure 1) in the crossbred population. Minor Allele Frequencies (MAF) in the F1 population
were variable for each cross breed and are outlined in Table 2. Two haplotype blocks were identified in the promoter region in these F1 populations;
comprising 4 SNPS in each (Figure 2). Linkage disequilibrium was not significant between any of the SNPs in the promoter
region and the non-synonymous SNP I199V in the coding region in the crossbred populations (Figure 2).

Figure 1.Overview of SNPs in promoter region of PRKAG3 gene and outline of alternative transcripts.

The three major haplotypes were identified in the promoter region; AGACAGCA, GAGTGAGG
and GAGTAGGG which accounted for 80% of the total variation in the Large White, 90%
in the Pietrain and 93% in Duroc (Table 3). Genotypes at the g.-995A>G and g.-311A>G loci permitted resolution of these three
major promoter haplotypes in all three F1 populations.

Genotypes were tested for association with PRKAG3 gene expression. A significant association (P =0.03) was observed between genotype at the g.-311A>G position and PRKAG3 gene expression in the Large White breed. AA genotypes displayed the lowest gene
expression (Mean = 0.31, ± 0.03), heterozygotes intermediate (Mean = 0.43, ± 0.04)
and GG the highest (Mean = 0.51, ± 0.06). No association between the g.-995A>G SNP
and gene expression was observed in any cross breed.

Genotyping of tagging SNP’s in larger purebred populations

Genotypes were obtained for 2 SNPs in the promoter region (g.-995A>G and g.-311A>G)
and the previously reported non-synonymous SNP I199V in three purebred populations. SNPs g.-995A>G and g.-311A>G in the promoter region
were polymorphic in the Large White (Minor Allele Frequency (MAF): 0.25 and 0.24 respectively)
and Duroc (MAF: 0.49 and 0.29 respectively) breeds. Pietrain animals were almost completely
monomorphic for both these SNPs (MAF, 0.051 and 0.053, respectively). All breeds were
polymorphic at the I199V locus. Linkage disequilibria plots showed no significant linkage disequilibrium between
the two tagging SNPs in the promoter region and the I199V SNP in either the crossbred (Figure 2) or purebred (Figures 3 & 4) populations. Genotype frequencies were in agreement with Hardy Weinberg equilibrium.

Figure 3.Output from Haploview including linkage disequilibrium (LD) plots indicating r2 values for SNPs in the regulatory region and inferred haplotypes for purebred Large
White population (n = 98).

I199V and associations with GP traits and IMF%

SNP I199V was associated with a number of GP-influenced traits in all three pure breeds (Table
4). The association with driploss% was observed in all breeds, where the II genotype
had the lowest driploss% and the VV genotype had the highest driploss%. The effect
was additive in all breeds, a 47%, 54% and 31% decrease in driploss% was observed
from VV to II, in Large White, Duroc and Pietrain breeds respectively. In the Duroc
breed, there was a small but significant additive association with ultimate pH at
24 hr in the M. semimembranosus muscle (pHUSM), with the II genotype having the highest and VV the lowest pH values.
In the Pietrain breed, there were associations with electrical conductivity in the
SM muscle (ECUSM), again the effect was additive with a 22% reduction in conductivity
from VV to II. Minolta a* was associated with I199V in this breed, the heterozygote AG genotype had a lower colour score (~26%) compared
to both homozygotes.

SNP I199V was associated with IMF% in the LTL muscle in both Large White and Pietrain breeds.
The II genotype had the highest IMF% and VV the lowest in both breeds. The effect
was additive, with a 37% and 29.4% decrease in IMF% from the II to VV genotype, in
Large White and Pietrain, respectively.

SNP g.-995A>G

The major allele (A) was fixed in the Pietrain breed. Association analysis of g.-995A>G
and meat quality traits in Large White and Duroc breeds are presented in Table 5. In the Large White breed this SNP was associated with a range of GP-influenced traits.
AA animals had a 34.5% decrease in driploss% relative to the alternative homozygote
(GG) genotype, with the AG genotype driploss% values intermediate. Samples with alternative
AA/GG genotypes thus differed by more than 1.2% in total driploss%. Similarly AA genotype
animals had higher pHULT, pH45LT, lower ECULT, and a tendency for lower Minolta L* and b* values. No significant
associations were observed in the Duroc population.

SNPg.-311A>G

There was almost complete linkage observed between g.-995A>G and g.-311A>G in the
purebred Large White breed population (Figure 3) and to a lesser degree in the purebred Duroc population (Figure 4). All significant associations with g.-311A>G were observed in the Large White breed
and mirror those reported for g.-995A>G.

Association analysis between PRKAG3 haplotypes for promoter SNPS and I199V and pork quality

Four major haplotypes comprising SNP g.-995A>G, SNPg.-311A>G and I199V were inferred by the Arlequin software [32]. Associations for all haplotypes and estimated least square means for meat traits
per haplotype copy are outlined for the Large White and Duroc Breeds in Tables 6 and 7 respectively. HAP2 was the most frequent haplotype in the Large White breed: (Freq:
0.47). All haplotypes were relatively evenly represented in the Duroc breed HAP1 (Freq:
0.19), HAP 2 (Freq: 0.28), HAP 3 (Freq: 0.28) and HAP4 (Freq: 0.21). As the promoter
SNPs were fixed in the Pietrain breed, haplotype association analysis was not performed
for this breed.

Table 6.Estimated least square means for significant meat quality traits in relation to copy
number of the most abundant porcine PRKAG3 gene haplotypes as inferred by Arlequin
for the promoter SNPs g.-995A>G and SNPg.-311A>G and non-synonymous SNP I199V locus in the Large White breed (n = 98)

Table 7.Estimated least square means for significant meat quality traits in relation to copy
number of the most abundant porcine PRKAG3 gene haplotypes as inferred by Arlequin for the promoter SNPs g.-995A>G and SNPg.-311A>G
and non-synonymous SNP I199V locus in the Duroc breed (n = 98)

HAP1 was associated with IMF% in the LTL muscle and driploss% in the Large White breed.
In the Duroc breed, HAP1 was associated with driploss% and pHUSM. In both breeds,
two copies of this haplotype had the most favourable effects on the associated phenotypes.

HAP2 was associated with IMF% in the LTL muscle, pHULT, pH45LT and pH45SM in the Large White breed. The presence of two copies of this haplotype had the
most favourable effect on these associated traits. No associations were observed for
HAP2 in the Duroc breed.

HAP3 was associated with driploss%, pHULT, pH45LT and b*Minolta in the Large White breed. The presence of two copies of this haplotype
had the least favourable effect on these traits. No associations were observed for
HAP3 in the Duroc breed.

HAP4 was present at too low a frequency (Freq: 0.01) in the Large White breed for
subsequent analysis. No associations were observed for HAP4 in the Duroc breed.

In-silico analysis of SNPs in relation to transcription factor binding sites in the
promoter region

In-silico analysis of the SNP loci using five transcription factor binding site (TFBS) prediction
tools (TFSEARCH, TESS, MatInspector, Match™ and ALIBABA2) is presented in Table 8. A CCAAT/enhancer binding protein site, encompassing the g.-995A>G site, was altered
to a GATA binding site on substitution to the minor allele. This change was identified
using all five tools.

Promoter assay

The three major promoter haplotypes outlined in (Table 3) used in the in vitro promoter assay accounted for approximately 90% of the variation within the three
breeds. Although no significant difference (P = 0.45) was observed between the haplotypes, transcriptional activity was established
in the region cloned when tested in vitro in pre-adipocytes (Figure 5).

Figure 5.The firefly luciferase values were normalised for total protein, and data is presented
relative to the empty vector control assigned a value of 1. The results are expressed as mean and the SE of three separate experiments performed
in quadruplicate. Statistical analysis was performed using one way ANOVA.

Discussion

In this study, PRKAG3 gene expression levels in porcine LTL muscle were correlated with a number of meat
quality phenotypes including GP-influenced traits and IMF%. As SNPs in the regulatory
region of a gene can influence the transcription rate [33], we explored the hypothesis that SNPs/inferred haplotypes in the PRKAG3 promoter would be associated with pork quality. This hypothesis was further validated
by identifying an association between g.-311A>G and PRKAG3 gene expression and by the significant associations identified between g.-995A>G,
g.-311A>G and quality traits pHULT, pH45LT, ECULT, driploss% and Minolta L* in the Large White pure bred population. The associations
with non-synonymous SNP I199V in this study served to validate the studied phenotypic model and provided a useful
comparator with which to view the novel promoter SNP associations. Inclusion of this
much studied SNP also indicated that the study had sufficient statistical power to
detect the influence of polymorphisms of moderate effect size. Ciobanu and colleagues
highlighted the complexity of the phenotype/genotype relationship in the PRKAG3 gene, proposing the model of “one gene-several polymorphisms-diverse phenotypes”
when describing the phenotypic effects of the non-synonymous SNPs identified in the
PRKAG3 gene [7]. Our data supports this model as the novel promoter SNPs were not in significant
linkage disequilibrium with the I199V locus, and exert different effects on phenotype which are independent from each other.
This adds to the complexity of the phenotype/genotype relationship, and indicates
that the additive effects of all these functionally distinct loci need to be considered
in future studies on pork quality.

In this study, the associations which were observed between the I199V locus and a number of GP-influenced traits were in concordance with the wider literature
in the breeds studied [7,13,17,19,22]. The association between I199V and IMF%, which was observed in both Large White and Pietrain breeds, is noteworthy
because there is a lack of consensus in the wider literature on the relationship between
I199V and IMF%. The association identified in our study, i.e. increasing IMF% from the
VV to II genotype, is in concordance with two studies that report the same trend in
a Korean native breed cross [26] and a Meishan cross [25]. The opposite trend was previously reported for a Landrace population [25] while several studies have reported a lack of association between I199V and IMF% [17,20,34]. Given the central role that AMPK has on all forms of energy metabolism, it is not surprising that variation that affects
the function of its regulatory component might impact on lipid deposition in muscle.
Associations between this gene region and lipid metabolism in muscle appear to be
evolutionarily conserved as AMPK/PRKAG3 is implicated as a molecular target to promote marbling in cattle [35] and triglyceride accumulation in mice [9].

The associations between PRKAG3 gene expression and both GP-influenced traits and IMF% suggests that not only are
protein structural modifications within the PRKAG3 coding region influencing the meat quality traits studied, but that variability in
the abundance of the transcript is also influential. This may be mediated by genetic
variation in promoter activity since SNP g.-311A>G was significantly associated with
gene expression. This hypothesis is further supported by the associations observed
between both g.-995A>G and g.-311A>G and GP-influenced traits i.e. pHULT, driploss%
and colour. Generally, the A allele in both promoter SNPs was associated both with
improved meat quality based on glycolytic traits and reduced PRKAG3 gene expression. HAP 2 and HAP 3 both have the same genotype V at the I199V locus
but differ with respect to their effects on Driploss%, further supporting the effects
of the promoter SNPs on phenotype. Drip loss is a significant challenge for the industry
[36,37] and these haplotypes are potentially relevant to selection strategies aimed at improving
this trait. Further to this, the promoter SNPs had highly significant associations
with pHULT (p = 0.0003) in the Large White breed, an association which was not observed with I199V. Interestingly in this study, the associations with GP-influenced phenotypes are
wider ranging and statistically more significant for the promoter SNPs than for I199V in the Large White breed. However, the associations with GP-influenced traits are
more consistent across breeds for the I199V SNP and of slightly larger magnitude with respect to driploss%. It is noteworthy
that in a recent study, a mouse model developed to over express AMPKγ reported a different phenotype to that expressing the gain of function variant of
AMPKγ with respect to mitochondrial biogenesis indicating that the phenotypic effects
of transcript abundance and mutations affecting protein function in PRKAG3 are not equivalent in skeletal muscle [38].

One of the modes by which SNPs in the regulatory region of a gene can influence transcription
rate is by forming or abolishing a TFBS [39]. In this study, the in-silico analysis suggested that g.-995A>G alters the associated
transcription factor-binding site from a putative CCAAT/enhancer binding protein site
to a putative GATA site on substitution to the minor allele. Both CCAAT/enhancer binding
protein and GATA transcription factors have been implicated as key regulators of adipocyte
differentiation and lipid metabolism [40], suggesting a potential role of this SNP in variation in IMF%. While g-311A>G was
not associated with a putative TFBS site, it is positioned in a highly conserved 5'
UTR, that contains several regulatory motifs characteristic of a core promoter [41]. 5' UTR regions have regulatory significance for translational efficiency and subsequent
phenotype [42]. The substitution of SNP at g.-311A>G may affect the core promoter and thus modulate
gene expression. This region also forms part of a 5' exon in the porcine transcriptome,
referred to as ‘exon zero’ [41]. Exon zero is contained in one of the two known alternative transcripts of the PRKAG3 gene. Hence based on in silico evidence it is possible that both these SNPs could have functional roles in the regulation
of PRKAG3, however associations with PRKAG3 gene expression were only observed for SNP g-311A>G and not g.-995A>G.

Taken together, the associations between PRKAG3 promoter haplotypes, gene expression and phenotype gene suggest the possibility of
differential promoter activity. While the promoter assay confirmed promoter activity
in the region cloned in all the major haplotypes, the assay was unable to discern
significant differences in transcriptional activity between the haplotypes in pre-adipocyte
cells. It is however worth re-iterating that the transcription of PRKAG3 is mainly ascribed to white skeletal muscle in humans and other species [5]. Furthermore the phenotypic associations observed were highly breed and tissue specific
indicating both a highly specific and finely tuned transcriptional apparatus. It is
therefore likely that changes in transcription rate mediated by variation in the transcription
binding sites may only be realised in vivo as evidenced by the association between genotype at the g-311A>G locus and PRKAG3 gene expression in the Large White cross.

In common with other recent porcine SNP association studies [29,43,44], the effects of putative functional SNPs can be breed and muscle specific. The effect
of these SNPs was certainly not consistent across breed and muscle type studied. Breed
seems to have important consequences for the phenotypic outcome of variation in both
the regulatory and coding regions of this gene, and this was particularly evident
for the promoter region. Alleles characterising HAP2 and HAP3 were associated with
GP-influenced traits in the Large White breed only. Most of the associations observed
in this study were seen in the LTL muscle. The relationship between muscle biochemistry
and meat quality phenotypes has been shown to differ for the LTL and SM muscle [45]. PRKAG3 gene expression is greater in LTL muscle [46] which displays more glycolytic traits compared to SM muscle [45]. In exercised trained pigs, carriers of the R200Q mutation has been shown to influence
the relative fibre composition to varying degrees among functionally different muscles,
thereby promoting a more oxidative phenotype [47]. With respect to the breed differences, the Large White has the largest percentage
of fast glycolytic fibres in the LT muscle relative to the Pietrain and the Duroc
breeds [45]. Hence, breed and muscle fibre type likely play interactive roles in defining the
penetrance of the novel alleles in the PRKAG3 promoter in relation to meat quality phenotypes.

While the overall goal of SNP/meat quality association studies is to provide markers
to improve quality parameters in breeding populations, it is becoming increasingly
apparent that there is significant breed variation in the potential for genetic improvement
based on fixation of particular haplotypes in certain breeds. It is of interest that
the I199V substitution effect on GP-influenced traits was conserved across all breeds, despite
their divergent muscle characteristics. In contrast the promoter allele effect was
apparent in the Large White breed, but not in the Duroc breed. This was also the case
for the associations between gene expression and phenotype. It is noteworthy that
the Duroc breed had superior meat quality characteristics as evidenced in earlier
work [45,48]. This is supported by previous studies, where substantial genetic variation has been
observed in IGF2 gene and the ANK1 gene regions in the Large White breed, but dramatically less in the Pietrain and
Duroc breeds [29,43]. While Duroc and Pietrain are terminal breeds, in which carcass characteristics are
the main selection criteria, the Large White breed is a maternal breed and therefore
may retain a higher degree of genotypic and phenotypic diversity for meat quality
traits. It is important to note however that there may have been a degree of ascertainment
bias in SNP discovery in this study, because the genetic contribution of the Large
White breed was approximately 33% in the Pietrain and Duroc cross-bred populations
which were used for SNP discovery.

Conclusions

To conclude, variation in the promoter region of the porcine PRKAG3 gene has associations with meat quality phenotypes, including traits which are influenced
by glycolytic potential and muscle metabolism in a breed-dependent manner. The novel
SNPs presented here, combined with the I199V SNP, represent a new opportunity to select for reduced drip loss in terminal Large
White sires based on combined novel genetic variation in the promoter, and known coding
SNP in the PRKAG3 gene. The lack of linkage disequilibrium observed between the promoter SNPs and the
I199V locus infer that their effects on phenotype are independent hence the additive effects
of all these loci should be considered in future studies on pork quality.

Methods

Animal resources

M. longissimus thoracis et lumborum (LTL) and M. semimembranosus (SM) tissues and blood were collected from two animal resources (86 crossbred and
295 purebred pigs) in which meat quality phenotypic data was available for a number
of traits as previously described [43,45,46,49]. The cross-bred resource comprised of 31 Large White-sired, 23 Duroc-sired and 32
Pietrain-sired F1 female offspring with a common Large White × Landrace background.
The purebred animals were females sampled from each of three closed populations (breeding
lines) based on Large White (n = 98), Duroc (n = 99) and Pietrain (n = 98) and all
reared in the same production system The purebred animals were reared in the same
conditions and fed the same diet and were slaughtered at 140 days with a live weight
of 109.56 ± 7.81 kg. [45]. The Pietrain line was homozygous dominant, NN (“Normal”) for the RYR1 [45,46].

PRKAG3 gene expression quantification

PRKAG3 gene expression was quantified in the LTL tissue samples which were collected from
the crossbred F1 animal resource for transcriptomic analysis. All tissue was taken
from approximately the same posterior location, in RNAse free conditions and preserved
in RNALater® (Ambion Ltd., Cambridge, UK) within 10 min post-exsanguination, snap-frozen
in dry ice, kept overnight at 4°C, and then stored at −20°C. RNA was extracted using
the Qiagen RNeasy® Fibrous Tissue Mini Kit (Qiagen, Hilden, Germany Ltd, West Sussex,
UK) according to the manufacturer’s instructions, together with a DNase treatment.
RNA integrity was assessed using the Bioanalyser 2100 RNA nano chip (Agilent Technologies,
Santa Clara, California, USA) and quantified with the NanoDrop 1000 Spectrophotometer
(Thermo Scientific, Waltham, MA).

Reverse transcription was carried out using total RNA to generate a cDNA template
for use with the QuantiTect SYBR Green PCR Kit (Qiagen, Hilden, Germany). For the
reverse transcription 2.5 μg of total RNA, 1 μl oligo (dT)12-18 (500 μg/ml), 1 μl
of a 10 mM dNTP mix were combined together in a final volume of 12 μl, heated at 65°C
for 5 min and then placed immediately on ice. The contents were collected by a brief
centrifugation before adding 4 μl 5X first strand buffer, 2 μl 0.1 M DTT, 1 μl SUPERase-In
(Ambion, Foster City) and 1 μl of Superscript III RNase H reverse transcriptase (200
u/μl) (Invitrogen, Carlsbad, CA). The reverse transcription was carried out at 50°C
for 1 h followed by an enzyme inactivation step of 70°C for 15 min. The cDNA was diluted
to 10 ng/μl for use as a template for quantitative PCR (qPCR).

All qPCR was performed on the Mx3000P™ Real-Time PCR System (Stratagene, La Jolla,
California, USA) using the QuantiTect™ SYBR Green Kit (Qiagen, Hilden, Germany). qPCR
reactions were carried out using 2X QuantiTect SYBR Green PCR Master mix, 1 μl of
10 mM sense and anti-sense gene specific primers, (final conc. 0.5 mM), 3 μl dH2O and 5 μl of total cDNA template (10 ng/ml) in a total volume of 20 μl. The thermal
profile was 95°C for 15 min, followed by 40 cycles of 94°C for 15 s, 60°C for 30 s
and 72°C for 30 s.

Reverse 5' GCCTGGCGAAGAATGGTGTTTC 3' and TATA box binding protein (TBP): [Genbank: DQ845178]: Forward: 5' TTAATGGTGGTGTTGTGGACGGC 3', Reverse: 5'CCAAATAGCAGCACAGTACGAGCAA
3'. These reference genes were previously found to be stable for gene expression analysis
in LTL muscle [50]. Stability was re-confirmed on these samples using Genorm [51]. PCR efficiencies (E) was calculated for each target PRKAG3 (99%), RPL4 (102%) and TBP (99.9%) and hence were suitable for comparison. The relative expression was calculated
according to an established protocol [52,53].

The promoter region of the PRKAG3 gene (1322 bp long) was sequenced in the crossbred F1 population.

Primers were designed from draft sequence of a BAC clone (GenBank Ref. AY263454) which
contained sequence flanking the PRKAG3 gene [41]. Primers were designed using the web based application Primer 3 [54].

Tagging SNP analysis

Based on patterns of linkage disequilibrium in crossbred animals, minor allele frequencies
and the ability to characterise haplotype blocks, two SNPs (g.-995A>G, g. SNP -311A>G)
in the promoter region and one in the coding region I199V were selected for association analysis in the three purebred populations. Genotyping
of SNPs g.-311A>G and I199V was performed using the Sequenom iPLEX assay (Sequenom, Hamburg, Germany). SNP g.-995A>G
was genotyped using a custom TaqMan assay, Assay ID: AHN1HPD (Applied Biosystems,
Warrington, UK).

Phenotypic analysis

Meat quality phenotypic information for LTL and SM were available for cross-bred samples
[49] and purebred samples [46] as previously described. pH and temperature at 45 min and 24 hr were measured in
cross-bred samples as detailed in [49] and in pure-bred animals according to [46]. For both sets of LTL samples, drip loss (driploss %) was determined after 3 days
according to the method of Honikel (1998) and expressed as a percentage of the initial
weight [56]. Percentage cooking loss (cookloss %) was measured in cross-bred samples only and
was determined by weighing transverse sections of the LTL before and after they were
heated to a core temperature of 75°C in a circulating water bath held at 77°C. Electrical
conductivity for both sets of samples was measured at a frequency of 1 KHz using a
Pork Quality Meter (PQM, INTEK, Aichach, Germany) in accordance with manufacturer’s
instructions. Bloomed CIE L* (lightness), a* (redness) and b* (yellowness) values
were determined in the LTL at 7 days post mortem in the cross-bred animals as detailed
in [49] and for pure-bred pigs at the last rib at 1 day post mortem using a Minolta C2002
Spectrophotometer (Minolta, Japan) as described in [46]. For cross-bred animals, intramuscular fat (IMF%) concentrations were determined
in thawed minced LTL samples using the Smart System 5 microwave moisture drying oven
and NMR Smart Trac Rapid Fat Analyser (CEM Corporation USA) using AOAC Official Methods
985.14 & 985.26, 1990. In purebred samples, IMF% levels in LTL and SM were assessed
using a Near Infrared Spectroscopy apparatus [46].

Promoter assay

The primers used to amplify the promoter region were modified (modification highlighted
in bold) at the 5' end to contain HIND III and BGL II restriction sites in the Forward:

The promoter region was amplified using 80 ng DNA, 45 μl Platinum High Fidelity Master
Mix (Invitrogen Carlsbad, California, USA) and 20 ng primer in a final volume of 50
μl. The PCR conditions were as follows 95°C, 5 min, and for 30 cycles; 95°C for 1
min, 60°C for 1 min and 72°C for 2 min. This was followed by a single step of 72°C
for 5 min. Samples were purified and quantified.

After 24 hr the media was removed and the cells washed with 500 μl of sterile phosphate
buffer saline. Lysis of the cells was performed by adding 200 μl of passive lysis
buffer (Promega Corp., Madison, WI, USA) followed by incubation at 37°C in a shaking
incubator for 30 min at 800 rpm. Luciferase activity was measured in 20 μl of cell
lysate after adding 100 μl luciferase assay reagent in a luminometer GLOMAX™, (Promega
Corp., Madison, WI, USA). All measurements were normalised to the total protein.

Identification of putative regulatory SNP’s in the PRKAG3 promoter region

Particular attention was paid to binding sites which changed on substitution to the
minor allele as well as sites known to be of relevance to mammalian muscle with high
similarity scores and matrix similarities.

Statistical methods

Haplotype analysis

Estimation of SNP frequencies and tests for departure from Hardy Weinberg equilibrium
were carried out using the Excel Microsatellite Toolkit [61] at each locus for each breed. Linkage disequilibrium and haplotype blocks were identified
using Haploview [62]. Following haplotype inference the ELB algorithm was used to assign the most likely
haplotype combination to each individual animal as implemented using Arlequin [32].

Association analysis

The relationship between normalised expression of PRKAG3 and meat quality traits was calculated using Pearson correlation in PASW Statistics
18.0 software (SPSS, Inc., Somers, NY, USA). Association analysis was carried between
genotyped SNPs/haplotypes and values of meat and carcass quality traits in each breed
using the least square means method of GLM (General Linear Model) procedure in SAS
(version 9.1; SAS Institute, Cary, NC, USA). Slaughter date was included in the model
as a covariate. Each analysis tested for a difference in least square means of meat
and carcass quality traits where 0, 1, or 2 copies of each haplotype were present.

The significance of the in vitro reporter assay across the three haplotypes and the association between genotypes
and PRKAG3 expression were established using One-Way ANOVA, in PASW Statistics 18.0 software
(SPSS, Inc., Somers, NY, USA).

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

MR carried out laboratory work, collation of data analysis, bioinformatic and population
data analysis and prepared the first draft of the manuscript. AH, CM and RMH carried
out laboratory work relating to DNA purification, qPCR and TaqMan genotyping respectively.
JMB and MG were involved in determination of meat phenotypes for gene expression study
and association analysis respectively and OS contributed to determination of phenotypes
and DNA extraction. TS, RMH, AMM and GD designed and coordinated the study. TS, RMH
and MR edited the manuscript and participated in the development of the final draft.
All authors agreed with the final manuscript.

Acknowledgements

The authors acknowledge Genus Plc/PIC US for provision of gDNA samples from purebred
Large White, Pietrain and Duroc pigs. The authors would also like to acknowledge Ms
Paula Reid (Teagasc, Ashtown) for help with data analysis, Mr Peadar Lawlor (Teagasc,
Moorepark) for supply of animals and Dr Bojlul Bahar for his help with promoter assay
development and optimisation. Funding for this research was provided under the National
Development Plan, through the Food Institutional Research Measure, administered by
the Department of Agriculture, Fisheries & Food, Ireland.